Feasibility and Validity of Computed Tomography-Derived Fractional Flow Reserve in Patients With Severe Aortic Stenosis: The CAST-FFR Study

BACKGROUND: Coronary artery disease is common in patients with severe aortic stenosis. Computed tomography-derived fractional flow reserve (CT-FFR) is a clinically used modality for assessing coronary artery disease, however, its use has not been validated in patients with severe aortic stenosis. This study assesses the safety, feasibility, and validity of CT-FFR in patients with severe aortic stenosis. METHODS: Prospectively recruited patients underwent standard-protocol invasive FFR and coronary CT angiography (CTA). CTA images were analyzed by central core laboratory (HeartFlow, Inc) for independent evaluation of CT-FFR. CT-FFR data were compared with FFR (ischemia defined as FFR ≤0.80). RESULTS: Forty-two patients (68 vessels) underwent FFR and CTA; 39 patients (92.3%) and 60 vessels (88.2%) had interpretable CTA enabling CT-FFR computation. Mean age was 76.2±6.7 years (71.8% male). No patients incurred complications relating to premedication, CTA, or FFR protocol. Mean FFR and CT-FFR were 0.83±0.10 and 0.77±0.14, respectively. CT calcium score was 1373.3±1392.9 Agatston units. On per vessel analysis, there was positive correlation between FFR and CT-FFR (Pearson correlation coefficient, R=0.64, P<0.0001). Sensitivity, specificity, positive predictive value, and negative predictive values were 73.9%, 78.4%, 68.0%, and 82.9%, respectively, with 76.7% diagnostic accuracy. The area under the receiver-operating characteristic curve for CT-FFR was 0.83 (0.72-0.93, P<0.0001), which was higher than that of CTA and quantitative coronary angiography (P=0.01 and P<0.001, respectively). Bland-Altman plot showed mean bias between FFR and CT-FFR as 0.059±0.110. On per patient analysis, the sensitivity, specificity, positive predictive, and negative predictive values were 76.5%, 77.3%, 72.2%, and 81.0% with 76.9% diagnostic accuracy. The per patient area under the receiver-operating characteristic curve analysis was 0.81 (0.67-0.95, P<0.0001). CONCLUSIONS: CT-FFR is safe and feasible in patients with severe aortic stenosis. Our data suggests that the diagnostic accuracy of CT-FFR in this cohort potentially enables its use in clinical practice and provides the foundation for future research into the use of CT-FFR for coronary evaluation pre-aortic valve replacement

Neo-LVOT and Transcatheter Mitral Valve Replacement: Expert Recommendations

With the advent of transcatheter mitral valve replacement (TMVR), the concept of the neo-left ventricular outflow tract (LVOT) was introduced and remains an essential component of treatment planning. This paper describes the LVOT anatomy and provides a step-by-step computed tomography methodology to segment and measure the neo-LVOT while discussing the current evidence and outstanding challenges. It also discusses the technical and hemodynamic factors that play a major role in assessing the neo-LVOT. A summary of expert-based recommendations about the overall risk of LVOT obstruction in different scenarios is presented along with the currently available methods to reduce the risk of LVOT obstruction and other post-procedural complications

Evaluation of an Artificial Intelligence Coronary Artery Calcium Scoring Model from Computed Tomography

OBJECTIVES: Coronary artery calcium (CAC) scores derived from computed tomography (CT) scans are used for cardiovascular risk stratification. Artificial intelligence (AI) can assist in CAC quantification and potentially reduce the time required for human analysis. This study aimed to develop and evaluate a fully automated model that identifies and quantifies CAC. METHODS: Fully convolutional neural networks for automated CAC scoring were developed and trained on 2439 cardiac CT scans and validated using 771 scans. The model was tested on an independent set of 1849 cardiac CT scans. Agatston CAC scores were further categorised into five risk categories (0, 1–10, 11–100, 101–400, and > 400). Automated scores were compared to the manual reference standard (level 3 expert readers). RESULTS: Of 1849 scans used for model testing (mean age 55.7 ± 10.5 years, 49% males), the automated model detected the presence of CAC in 867 (47%) scans compared with 815 (44%) by human readers (p = 0.09). CAC scores from the model correlated very strongly with the manual score (Spearman’s r = 0.90, 95% confidence interval [CI] 0.89–0.91, p < 0.001 and intraclass correlation coefficient = 0.98, 95% CI 0.98–0.99, p < 0.001). The model classified 1646 (89%) into the same risk category as human observers. The Bland–Altman analysis demonstrated little difference (1.69, 95% limits of agreement: −41.22, 44.60) and there was almost excellent agreement (Cohen’s κ = 0.90, 95% CI 0.88–0.91, p < 0.001). Model analysis time was 13.1 ± 3.2 s/scan. CONCLUSIONS: This artificial intelligence–based fully automated CAC scoring model shows high accuracy and low analysis times. Its potential to optimise clinical workflow efficiency and patient outcomes requires evaluation. KEY POINTS: • Coronary artery calcium (CAC) scores are traditionally assessed using cardiac computed tomography and require manual input by human operators to identify calcified lesions. • A novel artificial intelligence (AI)–based model for fully automated CAC scoring was developed and tested on an independent dataset of computed tomography scans, showing very high levels of correlation and agreement with manual measurements as a reference standard. • AI has the potential to assist in the identification and quantification of CAC, thereby reducing the time required for human analysis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-022-09028-3

Rationale and design of SAVI-AoS:A physiologic study of patients with symptomatic moderate aortic valve stenosis and preserved left ventricular ejection fraction

Background: Moderate aortic valve stenosis occurs twice as often as severe aortic stenosis (AS) and carries a similarly poor prognosis. Current European and American guidelines offer limited insight into moderate AS (MAS) patients with unexplained symptoms. Measuring valve physiology at rest while most patients experience symptoms during exertion might represent a conceptual limitation in the current grading of AS severity. The stress aortic valve index (SAVI) may delineate hemodynamically significant AS among patients with MAS. Objectives: To investigate the diagnostic value of SAVI in symptomatic MAS patients with normal left ventricular ejection fraction (LVEF ≥ 50%): aortic valve area (AVA) > 1 cm2 plus either mean valve gradient (MG) 15–39 mmHg or maximal aortic valve velocity (AOV max) 2.5–3.9 m/s. Short-term objectives include associations with symptom burden, functional capacity, and cardiac biomarkers. Long-term objectives include clinical outcomes. Methods and results: Multicenter, non-blinded, observational cohort. AS severity will be graded invasively (aortic valve pressure measurements with dobutamine stress testing for SAVI) and non-invasively (echocardiography during dobutamine and exercise stress). Computed tomography (CT) of the aortic valve will be scored for calcium, and hemodynamics simulated using computational fluid dynamics. Cardiac biomarkers and functional parameters will be serially monitored. The primary objective is to see how SAVI and conventional measures (MG, AVA and Vmax) correlate with clinical parameters (quality of life survey, 6-minute walk test [6MWT], and biomarkers). Conclusions: The SAVI-AoS study will extensively evaluate patients with unexplained, symptomatic MAS to determine any added value of SAVI versus traditional, resting valve parameters

Undetectable mannose binding lectin and corticosteroids increase serious infection risk in Rheumatoid Arthritis

Background: Infection is the leading cause of death in rheumatoid arthritis (RA). Corticosteroid (CS) use is a known and important risk factor for serious infections (SIs). Mannose binding lectin (MBL) is a genetically determined component of the innate immune system implicated in neonatal infections. Objective: Our aim was to determine whether MBL deficiency is a risk factor for SIs in RA and to compare it with CS use and also synthetic and biologic disease-modifying antirheumatic drug (DMARD) therapy. Methods: Data on 228 patients with RA were collected for up to 7 years (median = 5.9 years). Serum MBL concentrations were determined in all patients receiving synthetic (n = 96) or biologic (n = 132) DMARD therapy. Results: High rates of SIs were observed in RA irrespective of treatment (17%). Similar rates of SIs were observed in synthetic and biologic DMARD users. The rates of single and multiple Sis were similar, irrespective of the use of a biologic agent. Undetectable MBL (\u3c56 ng/mL) concentrations and maintenance prednisolone at 10 mg per day or higher were associated with an increased risk for an SI, with incident risk ratio of 4.67 (P = .001) and 4.70 (P \u3c .001), respectively. Conclusions: Undetectable MBL and prednisolone confer a high risk for an SI. The use of biologic DMARDs did not confer substantial SI risk in this observational study. MBL deficiency is hitherto an unrecognized risk factor for an SI in RA

Randomised clinical trial using Coronary Artery Calcium Scoring in Australian Women with Novel Cardiovascular Risk Factors (CAC-WOMEN Trial): study protocol

Introduction: Cardiovascular disease (CVD) is the leading cause of death in women around the world. Aboriginal and Torres Strait Islander women (Australian Indigenous women) have a high burden of CVD, occurring on average 10–20 years earlier than non-Indigenous women. Traditional risk prediction tools (eg, Framingham) underpredict CVD risk in women and Indigenous people and do not consider female-specific ‘risk-enhancers’ such as hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM) and premature menopause. A CT coronary artery calcium score (‘CT-calcium score’) can detect calcified atherosclerotic plaque well before the onset of symptoms, being the single best predictor for future cardiac events. A CT-calcium score may therefore help physicians intensify medical therapy in women with risk-enhancing factors. Methods and analysis: This multisite, single-blind randomised (1:1) controlled trial of 700 women will assess the effectiveness of a CT-calcium score-guided approach on cardiovascular risk factor control and healthy lifestyle adherence, compared with standard care. Women without CVD aged 40–65 (35–65 for Aboriginal and Torres Strait Islander women) at low-intermediate risk on standard risk calculators and with at least one risk-enhancing factor (eg, HDP, GDM, premature menopause) will be recruited. Aboriginal and Torres Strait Islander women will be actively recruited, aiming for ~10% of the sample size. The 6-month coprimary outcomes will be low-density lipoprotein cholesterol and systolic blood pressure. Barriers and enablers will be assessed, and a health economic analysis performed. Ethics and dissemination: Western Sydney Local Health District Research Ethics Committee (HREC 2021/ETH11250) provided ethics approval. Written informed consent will be obtained before randomisation. Consent will be sought for access to individual participant Medicare Benefits Schedule, Pharmaceutical Benefits Scheme claims usage through Medicare Australia and linked Admitted Patient Data Collection. Study results will be disseminated via peer-reviewed publications and presentations at national and international conferences. Trial registration number: ACTRN12621001738819p.Simone Marschner, Edwina Wing-Lun, Clara Chow, Louise Maple-Brown, Sian Graham, Stephen J Nicholls, Alex Brown, Anna Wood, Abdul Ihdayhid, Amy Von Huben, Sarah Zama

Clinical Applications of Mixed Reality and 3D Printing in Congenital Heart Disease

Understanding the anatomical features and generation of realistic three-dimensional (3D) visualization of congenital heart disease (CHD) is always challenging due to the complexity and wide spectrum of CHD. Emerging technologies, including 3D printing and mixed reality (MR), have the potential to overcome these limitations based on 2D and 3D reconstructions of the standard DICOM (Digital Imaging and Communications in Medicine) images. However, very little research has been conducted with regard to the clinical value of these two novel technologies in CHD. This study aims to investigate the usefulness and clinical value of MR and 3D printing in assisting diagnosis, medical education, pre-operative planning, and intraoperative guidance of CHD surgeries through evaluations from a group of cardiac specialists and physicians. Two cardiac computed tomography angiography scans that demonstrate CHD of different complexities (atrial septal defect and double outlet right ventricle) were selected and converted into 3D-printed heart models (3DPHM) and MR models. Thirty-four cardiac specialists and physicians were recruited. The results showed that the MR models were ranked as the best modality amongst the three, and were significantly better than DICOM images in demonstrating complex CHD lesions (mean difference (MD) = 0.76, p = 0.01), in enhancing depth perception (MD = 1.09, p = 0.00), in portraying spatial relationship between cardiac structures (MD = 1.15, p = 0.00), as a learning tool of the pathology (MD = 0.91, p = 0.00), and in facilitating pre-operative planning (MD = 0.87, p = 0.02). The 3DPHM were ranked as the best modality and significantly better than DICOM images in facilitating communication with patients (MD = 0.99, p = 0.00). In conclusion, both MR models and 3DPHM have their own strengths in different aspects, and they are superior to standard DICOM images in the visualization and management of CHD